MUSCLE and BLACK CAT in GAMEX ’17 Exercise

Robotic Capabilities in Naval Mine Clearance Tested
The NATO Research Vessel ALLIANCE (one of two such vessels owned and operated by NATO’s Centre for Maritime Research and Experimentation (CMRE) will be carrying two similar but distinct robotic vessels on board as part of the Centre’s first scientific campaign for 2017.

MUSCLE is a prototype unmanned underwater vessel (UUV) developed by CMRE for seabed mapping with automatic behaviour capabilities. BLACK CAT (derived from Collaborative Autonomy Testbed) is a UUV aimed at testing target reacquisition capabilities. Both will be evaluated during the Greek ARIADNE Mine Countermeasure Experiment 2017 (GAMEX’17) 28 March to 7 April.

During GAMEX ‘17, BLACK CAT will revisit targets detected acoustically detected by the MUSCLE, with its three sensors; a 2.25MHz Blueview downward-looking multibeam echosounder; a forward-looking 900kHz Blueview multibeam echosounder; and a camera. This will enable further research on autonomous behaviour for target reacquisition, 3D target reconstruction and  identification, and obstacle avoidance. In the long term, the CAT will be available for national integration of additional side-looking sensors or further test and experimentation.

The CAT tests contribute to the main GAMEX ‘17 goal; development of advanced methods for using robotics in mine countermeasures (MCM) in a diverse and challenging environment.  Being part of the live ARIADNE exercise, the experiment also makes it possible to benchmark robotic mine-hunting with conventional systems, thus  facilitating future technological transfer to operations. Interoperability and multi-vehicle collaboration are being highlighted, both to accelerate the detection, classification and identification timeline and to improve autonomous localisation capabilities through underwater communications. Networks of heterogeneous, self-organising robots will be put to the test, in order to achieve better and more rapid MCM missions.  The Italian Navy’s REMUS AUV team will also participate in the evaluation.

Publish date

03/30/2017

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